Public health surveillance programs using consensus sequencing (genotyping) estimate that at least one in ten antiretroviral (ARV)-nave persons infected with HIV-1 in the United States acquires drug resistant HIV-1. Guidelines therefore recommend resistance testing at the time of entry into care. However, consensus sequencing cannot detect low-frequency variants at levels below 10-50% of the viral population. The oligonucleotide ligation assay (OLA) is a more-sensitive assay that can detect mutations occurring in as little as 5% of the viral quasi-species. In a pilot study conducted among subjects with primary HIV-1 infection enrolled at the University of Washington Primary Infection Clinic (PIC), consensus sequencing detected transmitted HIV-1 drug resistance in 6% of 100 subjects, and OLA detected low-frequency mutations in 28 (30%) of 94 subjects who did not have mutations identified by consensus sequencing. We propose studies that will use OLA to address questions pertaining to the transmission and subsequent consequences of HIV-1 drug resistance. In Aim #1, we will study ARV-nave PIC subjects to compare the duration of detection (persistence) and level of detection of transmitted HIV-1 drug resistance over time in peripheral blood mononuclear cells (PBMCs), blood and seminal plasma. In Aim #2, we will study PIC subjects initiating ARV therapy and use OLA to determine whether additional mutations can be detected in PBMCs during successful treatment due to the selection of transmitted low-frequency drug resistance mutations or the development of new mutations. In Aim #3, we will use OLA to compare HIV-1 drug resistance patterns in PIC subjects and their source partners to determine whether HIV-1 drug resistance impacts transmission fitness. These novel investigations would broaden our understanding of the natural history and clinical impact of low- frequency HIV-1 drug resistance and inform guidelines for the testing and treatment of HIV-infected persons. If more-sensitive HIV-1 drug resistance assays were to be endorsed for clinical care before there is a full understanding of the relevance of low-frequency mutations, the potential increase in the complexity of initial ARV regimens and subsequent reduction in patient adherence could paradoxically increase the prevalence of drug resistance. Finally, empiric data from partner-pairs will generate information on correlates of HIV-1 transmission that could be incorporated into future models of the population dynamics of drug resistance. These models would estimate the overall proportion of HIV-1 drug resistance that is transmitted from ARV- nave source partners with primary HIV-1 infection versus ARV-experienced source partners with established HIV-1 infection. This data could be used to design public health interventions targeted to these populations to reduce the spread of transmitted HIV-1 drug resistance.